Name
Abstract | ||
|---|---|---|
AbstractIn this paper, we discuss the Kalman filter for state estimation in noisy linear discrete-timedynamical systems. We give an overview of its history, its mathematical and statisticalformulations, and its use in applications. We describe a novel derivation of the Kalman filterusing Newton's method for root finding. This approach is quite general as it can also be used toderive a number of variations of the Kalman filter, including recursive estimators for bothprediction and smoothing, estimators with fading memory, and the extended Kalman filter fornonlinear systems. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1137/100799666 | Periodicals |
Keywords | Field | DocType |
Kalman filter,state estimation,control theory,systems theory,Newton's method | Mathematical optimization,Extended Kalman filter,Alpha beta filter,Fast Kalman filter,Control theory,Algorithm,Filtering problem,Kalman filter,Unscented transform,Invariant extended Kalman filter,Ensemble Kalman filter,Mathematics | Journal |
Volume | Issue | ISSN |
54 | 4 | 0036-1445 |
Citations | PageRank | References |
7 | 0.78 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jeffrey Humpherys | 1 | 30 | 9.59 |
| Preston Redd | 2 | 7 | 0.78 |
| Jeremy M. West | 3 | 8 | 1.49 |